Literature DB >> 31236638

Artificial intelligence in intensive care: are we there yet?

Matthieu Komorowski1.   

Abstract

Mesh：

Year:  2019        PMID： 31236638     DOI： 10.1007/s00134-019-05662-6

Source DB:  PubMed          Journal:  Intensive Care Med        ISSN： 0342-4642            Impact factor:   17.440


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  12 in total

1.  Translating Artificial Intelligence Into Clinical Care.

Authors:  Andrew L Beam; Isaac S Kohane
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

2.  What's new in ICU in 2050: big data and machine learning.

Authors:  Sébastien Bailly; Geert Meyfroidt; Jean-François Timsit
Journal:  Intensive Care Med       Date:  2017-12-26       Impact factor: 17.440

3.  An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

Authors:  Shamim Nemati; Andre Holder; Fereshteh Razmi; Matthew D Stanley; Gari D Clifford; Timothy G Buchman
Journal:  Crit Care Med       Date:  2018-04       Impact factor: 7.598

4.  Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.

Authors:  Romain Pirracchio; Maya L Petersen; Marco Carone; Matthieu Resche Rigon; Sylvie Chevret; Mark J van der Laan
Journal:  Lancet Respir Med       Date:  2014-11-24       Impact factor: 30.700

5.  The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.

Authors:  Matthieu Komorowski; Leo A Celi; Omar Badawi; Anthony C Gordon; A Aldo Faisal
Journal:  Nat Med       Date:  2018-10-22       Impact factor: 53.440

6.  Six subphenotypes in septic shock: Latent class analysis of the PROWESS Shock study.

Authors:  Bengt Gårdlund; Natalia O Dmitrieva; Carl F Pieper; Simon Finfer; John C Marshall; B Taylor Thompson
Journal:  J Crit Care       Date:  2018-06-08       Impact factor: 3.425

Review 7.  High-performance medicine: the convergence of human and artificial intelligence.

Authors:  Eric J Topol
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

8.  Guidelines for reinforcement learning in healthcare.

Authors:  Omer Gottesman; Fredrik Johansson; Matthieu Komorowski; Aldo Faisal; David Sontag; Finale Doshi-Velez; Leo Anthony Celi
Journal:  Nat Med       Date:  2019-01       Impact factor: 53.440

Review 9.  State of the art review: the data revolution in critical care.

Authors:  Marzyeh Ghassemi; Leo Anthony Celi; David J Stone
Journal:  Crit Care       Date:  2015-03-16       Impact factor: 9.097

10.  Transcriptomic Signatures in Sepsis and a Differential Response to Steroids. From the VANISH Randomized Trial.

Authors:  David B Antcliffe; Katie L Burnham; Farah Al-Beidh; Shalini Santhakumaran; Stephen J Brett; Charles J Hinds; Deborah Ashby; Julian C Knight; Anthony C Gordon
Journal:  Am J Respir Crit Care Med       Date:  2019-04-15       Impact factor: 21.405
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  11 in total

1.  Clinical management of sepsis can be improved by artificial intelligence: no.

Authors:  José Garnacho-Montero; Ignacio Martín-Loeches
Journal:  Intensive Care Med       Date:  2020-02-03       Impact factor: 17.440

2.  Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.

Authors:  Jack Gallifant; Joe Zhang; Maria Del Pilar Arias Lopez; Tingting Zhu; Luigi Camporota; Leo A Celi; Federico Formenti
Journal:  Br J Anaesth       Date:  2021-11-09       Impact factor: 9.166

3.  Ignorance Isn't Bliss: We Must Close the Machine Learning Knowledge Gap in Pediatric Critical Care.

Authors:  Daniel Ehrmann; Vinyas Harish; Felipe Morgado; Laura Rosella; Alistair Johnson; Briseida Mema; Mjaye Mazwi
Journal:  Front Pediatr       Date:  2022-05-10       Impact factor: 3.569

4.  ERS International Congress 2021: highlights from the Respiratory Intensive Care Assembly.

Authors:  Aileen Kharat; Carla Ribeiro; Berrin Er; Christoph Fisser; Daniel López-Padilla; Foteini Chatzivasiloglou; Leo M A Heunks; Maxime Patout; Rebecca F D'Cruz
Journal:  ERJ Open Res       Date:  2022-05-23

5.  Improvements in Patient Monitoring in the Intensive Care Unit: Survey Study.

Authors:  Akira-Sebastian Poncette; Lina Mosch; Claudia Spies; Malte Schmieding; Fridtjof Schiefenhövel; Henning Krampe; Felix Balzer
Journal:  J Med Internet Res       Date:  2020-06-19       Impact factor: 5.428

6.  Clinical evaluation of an interoperable clinical decision-support system for the detection of systemic inflammatory response syndrome in critically ill children.

Authors:  Antje Wulff; Sara Montag; Nicole Rübsamen; Friederike Dziuba; Michael Marschollek; Philipp Beerbaum; André Karch; Thomas Jack
Journal:  BMC Med Inform Decis Mak       Date:  2021-02-18       Impact factor: 2.796

Review 7.  Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter.

Authors:  Davy van de Sande; Michel E Van Genderen; Jim M Smit; Joost Huiskens; Jacob J Visser; Robert E R Veen; Edwin van Unen; Oliver Hilgers Ba; Diederik Gommers; Jasper van Bommel
Journal:  BMJ Health Care Inform       Date:  2022-02

8.  Deep Learning-Based Pain Classifier Based on the Facial Expression in Critically Ill Patients.

Authors:  Chieh-Liang Wu; Shu-Fang Liu; Tian-Li Yu; Sou-Jen Shih; Chih-Hung Chang; Shih-Fang Yang Mao; Yueh-Se Li; Hui-Jiun Chen; Chia-Chen Chen; Wen-Cheng Chao
Journal:  Front Med (Lausanne)       Date:  2022-03-17

Review 9.  Contribution of CT-Scan Analysis by Artificial Intelligence to the Clinical Care of TBI Patients.

Authors:  Clément Brossard; Benjamin Lemasson; Arnaud Attyé; Jules-Arnaud de Busschère; Jean-François Payen; Emmanuel L Barbier; Jules Grèze; Pierre Bouzat
Journal:  Front Neurol       Date:  2021-06-10       Impact factor: 4.003

Review 10.  Machine Learning for Cardiovascular Outcomes From Wearable Data: Systematic Review From a Technology Readiness Level Point of View.

Authors:  Arman Naseri Jahfari; David Tax; Marcel Reinders; Ivo van der Bilt
Journal:  JMIR Med Inform       Date:  2022-01-19
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